Diseases in chili plants are a serious problem that can significantly reduce crop yields and production quality, making early detection essential to assist farmers. This study uses a Convolutional Neural Network (CNN) approach with Transfer Learning methods to classify diseases on chili plant leaves. Infected chili leaf image data is processed and trained using a pre-trained CNN model to improve classification accuracy, even with limited data. The results show that this approach successfully identifies various types of diseases on chili leaves with a high level of accuracy. This approach is expected to be an effective solution for the agricultural sector to achieve faster and more efficient plant disease detection.
Copyrights © 2024